{"title":"一种新的高效自适应多项式混沌展开元模型","authors":"Guangsong Chen, L. Qian, Jia Ma, Lei Ji","doi":"10.1109/AIM.2015.7222702","DOIUrl":null,"url":null,"abstract":"To address the challenge of the accuracy and efficiency of the metamodel, an adaptive sequential polynomial chaos expansion (ASPCE) metamodel technique is presented. The Latin hypercube sampling (LHS) is used to obtain the initial samples. A new adaptive truncation strategy of polynomial chaos expansion (PCE) is presented for high order PCE, and the parameters are updated by global sensitivity indices got by the Sobol' sensitivity analysis based on the PCE directly. The important terms of PCE are selected by elastic net (EN), and the samples are added according to the combined sequential criterion until the accuracy requirements are satisfied. Thus, by using the presented method, high accuracy model can be constructed by using small number of samples and the global sensitivity indices can be obtained efficiently. At last, three benchmark examples and a numerical example are provided to demonstrate the effectiveness and the efficiency of the presented method.","PeriodicalId":199432,"journal":{"name":"2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new efficient adaptive polynomial chaos expansion metamodel\",\"authors\":\"Guangsong Chen, L. Qian, Jia Ma, Lei Ji\",\"doi\":\"10.1109/AIM.2015.7222702\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To address the challenge of the accuracy and efficiency of the metamodel, an adaptive sequential polynomial chaos expansion (ASPCE) metamodel technique is presented. The Latin hypercube sampling (LHS) is used to obtain the initial samples. A new adaptive truncation strategy of polynomial chaos expansion (PCE) is presented for high order PCE, and the parameters are updated by global sensitivity indices got by the Sobol' sensitivity analysis based on the PCE directly. The important terms of PCE are selected by elastic net (EN), and the samples are added according to the combined sequential criterion until the accuracy requirements are satisfied. Thus, by using the presented method, high accuracy model can be constructed by using small number of samples and the global sensitivity indices can be obtained efficiently. At last, three benchmark examples and a numerical example are provided to demonstrate the effectiveness and the efficiency of the presented method.\",\"PeriodicalId\":199432,\"journal\":{\"name\":\"2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIM.2015.7222702\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Advanced Intelligent Mechatronics (AIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIM.2015.7222702","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A new efficient adaptive polynomial chaos expansion metamodel
To address the challenge of the accuracy and efficiency of the metamodel, an adaptive sequential polynomial chaos expansion (ASPCE) metamodel technique is presented. The Latin hypercube sampling (LHS) is used to obtain the initial samples. A new adaptive truncation strategy of polynomial chaos expansion (PCE) is presented for high order PCE, and the parameters are updated by global sensitivity indices got by the Sobol' sensitivity analysis based on the PCE directly. The important terms of PCE are selected by elastic net (EN), and the samples are added according to the combined sequential criterion until the accuracy requirements are satisfied. Thus, by using the presented method, high accuracy model can be constructed by using small number of samples and the global sensitivity indices can be obtained efficiently. At last, three benchmark examples and a numerical example are provided to demonstrate the effectiveness and the efficiency of the presented method.